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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Updated: May 22, 2026

Processing the Loblolly Pine PtGen2 cDNA Microarray

Processing the Loblolly Pine PtGen2 cDNA Microarray

Published on: March 20, 2009

Workflows for microarray data processing in the Kepler environment.

Thomas Stropp¹, Timothy McPhillips, Bertram Ludäscher

¹Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada.

BMC Bioinformatics

|May 19, 2012

Summary

This summary is machine-generated.

We developed adaptable bioinformatics pipelines for microarray data analysis using the Kepler workflow system. These tools simplify complex analyses and can be customized for specific research needs.

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Published on: March 20, 2009

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Microarray data analysis is complex, requiring specialized pipelines that are often difficult to modify or extend.
Scientific workflow systems offer general-purpose frameworks to streamline pipeline development and execution.
The Kepler workflow environment provides a flexible graphical interface and supports multiple programming languages for bioinformatics algorithm development.

Purpose of the Study:

To develop adaptable bioinformatics pipelines for common microarray data analysis tasks.
To leverage the Kepler workflow environment for creating user-friendly and customizable analysis tools.
To provide a foundation for future comparisons of different workflow systems in microarray data processing.

Main Methods:

Development of bioinformatics pipelines within the Kepler workflow environment.
Implementation of tools for GFF file processing of NimbleGen ChIP-chip datasets.
Creation of comprehensive workflows for Affymetrix gene expression microarray analysis and primer design.

Main Results:

A series of functional bioinformatics pipelines for microarray data processing were successfully developed in Kepler.
The developed pipelines include tools for ChIP-chip data, gene expression analysis, and primer design.
These workflows are designed to be easily customized, extended, and repurposed for specific research projects.

Conclusions:

A set of tools and complete workflows for microarray data analysis were provided within the Kepler environment.
The Kepler environment offers advantages such as a clear graphical display of analysis steps and parameters.
The workflows facilitate easy integration of external resources like remote data and web services.